Current issue
No 3/2025, September

Changes in the Slovak Plum Production and its Competitiveness on the Single Market

ABSTRACT

The article identifies the importance and development of production and related competitiveness in the EU single market of plum production in the Slovak Republic in the time horizon from Slovakia's accession to the EU until 2020. The research results show an overall positive development in the area of plum orchards (18% increase), which is in contrast to the overall development of the area of orchards in the Slovak Republic (7.12% decrease). However, the changes in the area under cultivation are not reflected in the increase in production (decrease of 45.22%) during the period under study. This fact was also reflected in the volatility of the identified competitiveness of Slovak plum production on the EU Single Market during the period under review. The trade balance was positive only to a limited extent in 2008 and 2009. Nevertheless, the measured RCA values point to a more significant degree of competitiveness of Slovak plum production on the EU single market, with a positive trend between 2008 and 2015. However, there is a decline in competitiveness after 2015, when this negative trend could not be reversed until the end of the period under consideration. In order to reverse this negative trend, further targeted measures will be necessary in the future, both in terms of policies, modernisation processes and improved agrotechnical practices.

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Shadow Values of Carbon Sequestration: A Case Study of the Czech Republic

ABSTRACT

This paper estimates the shadow values of total carbon sequestration in Czech cereal production. We use a production model with multiple outputs and inputs, using an input distance function (IDF) to estimate shadow price of land. The shadow prices of land and the amount of total carbon sequestration are then used to estimate the shadow values of carbon sequestration for a selected group of crops. The results present considerable differences in shadow values across both crops types and farm sizes.

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Fuzzy Logic for Yield Prediction: Enhancing Decision-Making in Agricultural Economics

ABSTRACT

Accurate yield prediction is essential for optimizing decision-making in agricultural economics, enabling stakeholders to manage resources efficiently and respond to market demands. Traditional yield prediction models often struggle to handle the uncertainties and complexities inherent in agricultural systems, such as weather variability, soil conditions, and crop characteristics. This study introduces a fuzzy logic-based approach to yield prediction, offering a more flexible and robust method for addressing these uncertainties. By utilizing fuzzy sets and rules, the proposed model captures the intricate relationships between multiple factors influencing crop yield. The research demonstrates how fuzzy logic can enhance the accuracy and reliability of yield predictions, providing valuable insights for farmers, policymakers, and agricultural economists. Results indicate that this approach significantly improves decision-making processes in agricultural planning and risk management, making it a valuable tool for sustainable agricultural practices.

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Management of Low Volume Roads: A Decision Support Tool for Sustainable Wildfire Prevention and Maintenance Resources Allocation Via GIS-Network Analysis

ABSTRACT

This study presents a GIS-based decision support system (DSS) for prioritizing forest road network maintenance to enhance wildfire prevention and suppression in Mediterranean forest regions. The research focuses on low-volume roads (LVRs), which play a critical role in fire response operations but often suffer from limited maintenance resources and accessibility constraints. Using GIS-based network analysis, the study integrates road hierarchization, wildfire risk modeling, and optimal route determination to develop a structured approach for forest road maintenance prioritization. The methodology involves segmenting and evaluating road networks based on travel time, slope, and fire risk exposure, enabling a data-driven ranking system that identifies critical access routes for emergency response. The study applies the Closest Facility method to determine optimal routes from firefighting vehicle stations to various locations within the network. Results indicate that a targeted maintenance strategy, prioritizing high-risk road sections, significantly improves fire response efficiency while optimizing resource allocation in financially constrained forest management frameworks. This approach introduces a sustainable and cost-effective framework for forest road infrastructure planning, offering a practical tool for decision-makers in fire-prone regions. By ensuring proactive maintenance scheduling, the proposed method enhances wildfire resilience, reduces emergency response delays, and supports long-term forest sustainability.

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Predictive Battery Life Modeling for LoRaWAN Sensors Using Real-World Deployment Data

ABSTRACT

This study presents a comprehensive analysis of LoRaWAN-based IoT communication in an agricultural monitoring context. The research is grounded in long-term experimental data collected from four environmental sensors deployed in the Czech Republic, focusing on temperature and humidity measurements. Beyond the environmental data, the study emphasizes the technical performance of the deployed devices, particularly in terms of signal quality and energy efficiency. We analyzed 14 key transmission parameters, including RSSI, SNR, Time on Air, and gateway reception metrics, to evaluate the communication reliability and network coverage. A significant contribution of this work is the development of a data-driven model for estimating battery life based on real-world usage patterns and spreading factor distributions. This model enables predictive maintenance planning and supports energy-efficient network design. The study builds on previous research and contributes to the growing body of literature on holistic performance evaluation in IoT systems.

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Does International Food Assistance Reduces Food Insecurity in Developing Countries?

ABSTRACT

Food assistance is one of the international commitments to reduce food insecurity in developing countries, but only a few studies have explored its effectiveness, especially in across multiple countries. The purpose of this study is to examine the impact of international food assistance on food insecurity in developing countries. I analysed 2001–2021 data from 70 developing countries across Africa, Asia and Europe, Latin America and the Caribbean using the system General Method of Moment (sys-GMM). Our study indicates that international food assistance reduces food insecurity in Africa but has no impact on other regions. Government effectiveness and agricultural imports can help to minimise food insecurity in the study areas. Food inflation and age dependency ratios increase food insecurity in developing countries, whereas other variables have different effects among regions.

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Determinants of Working Capital Management of Companies in Agriculture in the Czech Republic

ABSTRACT

The aim of the article is to evaluate determinants of working capital investment policy of companies in agriculture in the Czech Republic from 2013 to 2022. The aim of this article is to identify the main determinants that influence the management of working capital in agricultural enterprises in the Czech Republic and to analyze how these factors affect the operational efficiency and financial stability of these enterprises from 2013 to 2022. Comparative analysis, Granger causality test and generalized method of moments (GMM method) will be used to identify the determinants of working capital. The data base includes 2 516 enterprises operating in agriculture in the Czech Republic. The results showed that the agricultural sector has a relaxed investment policy with a high share of inventories, while in recent years there has been a positive improvement in the effectiveness of working capital management. This policy is significantly influenced by company size, growth opportunities and capital structure. The improvement in return on assets and equity contributed to better financial stability. Companies can optimize their investment policy and improve financial results through better analysis of these factors.

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Social Impacts, Capacity and Awareness on the Intention to Participate in the Digitalization of e-Agriculture on e-Commerce Platforms: A Case Study of Durian Households in Tien Giang Province, Vietnam

ABSTRACT

The study provides a new perspective for the entire investigation, providing an overview of the theoretical implications related to behavior, participation intent, and the digitization of e-agriculture on e-commerce platforms. In addition, the main point is the approach of durian farmers specifically in Tien Giang province, about the intention to participate in e-agriculture. This study presents relevant factors that have an impact on the intention to participate in e-agriculture, specifically durian farmers. From the actual situation of agriculture in the Mekong Delta, typically Tien Giang province. Especially the theoretical of agriculture, e-agriculture and the intention to participate in e-agriculture on the e-commerce platform, an empirical approach in Tien Giang province, Vietnam. The model proposes factors including Social Impact for Agriculture, Adaptive Capacity, Agriculture Awareness, Digitalizations of e-agriculture, e-agriculture on e-commerce has a positive impact on the intention to participate in e-agriculture on e-commerce platforms. This research data was surveyed by direct interviews with 210 durian farmers in Cai Be district of Tien Giang province. Research methods using PLS-SEM. The results of the study show that the factors that have an impact on the intention to participate in e-agriculture on the e-commerce platform: The case of durian farmers. From the fact that this study serves as a premise and proposes implications that are appropriate for further studies on the intention to participate in e-agriculture on the e-commerce platform, related to the intention to participate (e-agriculture) of farmers, especially durian fruit e-agricultural products. An experimental evidence in Tien Giang province, Vietnam.

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Gender-Inclusive Digital Literacy and Socioeconomic Resilience Among Smallholder Farmers: The Moderating Role of Trust in Technology in Food-Insecure Regions

ABSTRACT

Smallholder farmers in food-insecure regions face structural constraints that undermine household resilience, including gender disparities, limited digital access, and low trust in technology. This study develops and tests the Gender-Inclusive Digital Literacy for Women Empowerment (GIDL-WE) model to examine how gender inclusion, digital literacy, and trust in technology interact to influence socioeconomic resilience. Using survey data from 350 women in smallholder farming households in Central Kalimantan, Indonesia, the research employs Partial Least Squares–Structural Equation Modeling (PLS-SEM) for analysis. Results indicate that gender inclusion significantly enhances inclusive digital literacy (β = 0.285, p < 0.000), while digital literacy unexpectedly exerts a negative effect on socioeconomic resilience (β = –0.217, p < 0.000). Trust in technology has moderates the digital literacy–resilience link (β = 0.176, p < 0.000), suggesting that digital literacy yields benefits only when supported by high trust levels. The model explains 28.3% of the variance in socioeconomic resilience and demonstrates a satisfactory global fit (GoF = 0.39). These findings highlight the centrality of trust as a catalyst for translating digital inclusion into resilience, offering empirical insights for designing gender-responsive digital interventions in agriculture.

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Enhancing Agricultural Productivity and Food Security Through Climate Smart Agriculture (CSA) Adoption: The Interplay of Social, Economic and Environmental in Tidal Swamp Farming

ABSTRACT

Food security is closely linked to agricultural productivity and the adoption of modern technologies. This study examines the socio-economic and environmental factors that drive the adoption of Climate-Smart Agriculture (CSA), enhance productivity, and improve food security in tidal swamp areas. The interrelationships between economic factors such as income and access to capital, and environmental factors like sustainable land management practices and water resource usage, all of which play a crucial role in the adoption of CSA technologies. The study was conducted with 180 farmers in Banyuasin Regency, specifically in Telang Makmur, Panca Mukti and Telang Jaya Villages, who provided data to assess how these factors influence food security outcomes. The findings indicate that both economic and environmental factors significantly affect the adoption of CSA technology, which subsequently leads to increased agricultural productivity and food security. Specifically, economic empowerment through higher income levels and enhanced access to capital enables farmers to invest in CSA technologies, while environmentally sustainable practices help mitigate climate risks and improve land and water management. The results underscore the importance of integrated approaches that address both economic and environmental dimensions to ensure long-term food security. This study provides valuable insights for policymakers, stressing the need for strategies that combine economic support, technological innovation, and environmental sustainability to enhance food security in regions like Muara Telang.

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